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Flawfinder output manipulation via untrusted filenames and source text

High severity GitHub Reviewed Published May 23, 2026 in david-a-wheeler/flawfinder • Updated Aug 11, 2026

Package

pip flawfinder (pip)

Affected versions

< 2.0.20

Patched versions

2.0.20

Description

Impact

This vulnerability is an improper input neutralization issue leading to output manipulation, specifically, Terminal/ANSI Escape Sequence Injection and XML Injection:

  • Terminal Output Spoofing: A malicious file whose name contains ANSI escape sequences can end up being included in flawfinder's standard terminal output, with many effects. For example, this might allow an attacker to hide critical scan results, falsely making it appear to a human reviewer that no security issues were found.

  • CSV and XML Injection: Untrusted fields (such as filenames, categories, or code context text) were not properly sanitized when generating structured reports. An attacker could exploit this to corrupt CSV formats or inject arbitrary XML attributes into SonarQube outputs via output_sonar().

It impacts those who use flawfinder to evaluate intentionally malicious filenames or file contents.

The initial filename injection problem was reported by Dan Lenz https://www.linkedin.com/in/dan-lenz/

The other vulnerabilities were found by flawfinder project leader David A. Wheeler, GitHub david-a-wheeler, https://dwheeler.com/

Patches

This issue has been fully patched in Version 2.0.20 (released 2026-05-16). All users should upgrade to version 2.0.20 or later immediately. If you use Python's package manager, you can upgrade using pip install --upgrade flawfinder. If you are consuming flawfinder via GitHub Actions, ensure your workflow points to david-a-wheeler/flawfinder@2.0.20 or later.

Workarounds

There is no configuration-based workaround within older versions of flawfinder. If an immediate upgrade is not possible, users can mitigate the risk by:

  • Pre-scanning filenames: Manually or programmatically verifying that target repositories do not contain filenames with control characters (including ANSI escape sequences) before passing them to flawfinder.

  • Inspecting raw output: Reviewing flawfinder outputs in a text editor or logging mechanism that explicitly displays or strips raw escape sequences, rather than relying on live terminal rendering.

  • Restricting untrusted inputs: Avoiding the generation of SonarQube or CSV reports from completely untrusted repositories until the tool is updated.

Resources

See the flawfinder GitHub Repository: https://github.com/david-a-wheeler/flawfinder

References

@david-a-wheeler david-a-wheeler published to david-a-wheeler/flawfinder May 23, 2026
Published to the GitHub Advisory Database Jun 26, 2026
Reviewed Jun 26, 2026
Last updated Aug 11, 2026

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity High
Availability None
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N

EPSS score

Weaknesses

Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection')

The product constructs all or part of a command, data structure, or record using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify how it is parsed or interpreted when it is sent to a downstream component. Learn more on MITRE.

CVE ID

CVE-2026-48813

GHSA ID

GHSA-4c3c-r6p8-c863

Source code

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